![]() All functions in the toolbox can work both on data matrices as on PRTools datasets (). It will create a helix dataset, estimate the intrinsic dimensionality of the dataset, run Laplacian Eigenmaps on the dataset, and plot the results. MappedX = compute_mapping(X, 'Laplacian', no_dims, 7) įigure, scatter(mappedX(:,1), mappedX(:,2), 5, labels) title('Result of dimensionality reduction'), drawnow ![]() No_dims = round(intrinsic_dim(X, 'MLE')) ĭisp() The graphical user interface of the toolbox is accessible through the DRGUI function.īasically, you only need one function: mappedX = compute_mapping(X, technique, no_dims) In addition to these techniques, the toolbox contains functions for prewhitening of data (the function PREWHITEN), exact and estimate out-of-sample extension (the functions OUT_OF_SAMPLE and OUT_OF_SAMPLE_EST), and a function that generates toy datasets (the function GENERATE_DATA). Estimator based on geodesic minimum spanning tree ('GMST') Estimator based on packing numbers ('PackingNumbers') Estimator based on nearest neighbor evaluation ('NearNb') ![]() Estimator based on correlation dimension ('CorrDim') Eigenvalue-based estimation ('EigValue') These techniques are available through the function INTRINSIC_DIM. Autoencoders using evolutionary optimization ('AutoEncoderEA')įurthermore, the toolbox contains 6 techniques for intrinsic dimensionality estimation. Autoencoders using stack-of-RBMs pretraining ('AutoEncoderRBM') Gaussian Process Latent Variable Model ('GPLVM') Fast Maximum Variance Unfolding ('FastMVU') Landmark Maximum Variance Unfolding ('LandmarkMVU') Maximum Variance Unfolding ('MVU', implemented as an extension of LLE) Conformal Eigenmaps ('CCA', implemented as an extension of LLE) Linear Local Tangent Space Alignment ('LLTSA') Linearity Preserving Projection ('LPP') Neighborhood Preserving Embedding ('NPE') t-Distributed Stochastic Neighbor Embedding ('tSNE') Symmetric Stochastic Neighbor Embedding ('SymSNE') Generalized Discriminant Analysis ('KernelLDA') These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. This Matlab toolbox implements 32 techniques for dimensionality reduction. In order to compile all MEX-files, type cd() in your Matlab prompt, and execute the function MEXALL. Precompiled versions of these MEX-files are distributed with this release, but the compiled version for your platform might be missing. ![]() Some of the functions in the toolbox use MEX-files. Subsequently, press the Save button in order to save your changes to the Matlab search path. Click the 'Add with subfolders.' button, select the folder $MATLAB_DIR/toolbox/drtoolbox in the file dialog, and press Open. Start Matlab and select 'Set path.' from the File menu. Up to date sources are available in peazip-sources Git directory, and snapshots of the source code at each x.y.z release are available in Releases as peazip-x.y.z.src.zip packages, with (featured both in Git and in source packages) containing detailed instructions for compiling the application and building packages for different systems.Matlab Toolbox for Dimensionality Reduction (v0.7.1b)Īffiliation: University of California, San Diego / Delft University of TechnologyĬopy the drtoolbox/ folder into the $MATLAB_DIR/toolbox directory (where $MATLAB_DIR indicates your Matlab installation directory). The program is written in Lazarus/FreePascal (Windows installable packages are scripted with InnoSetup, with Pascal-like syntax) and offers a LGPLv3 alternative to proprietary software (WinZip, WinRar, etc), running as native application on Windows/Win64, Wine/ReactOS, Linux x86/x86-64 (with Linux ARM and BSD ports also available), and Darwin/macOS both Intel x86_64 and aarch64 (e.g. The project aims to provide a cross-platform, portable, GUI frontend for multiple Open Source technologies (7-Zip, FreeArc, PAQ/ZPAQ, PEA, UPX, Brotli, Zstd) focused on file and archive management, and security (strong encryption, two factor authentication, encrypted password manager, secure delete). PeaZip is a free file archiver utility and rar extractor for Linux, macOS, and Windows, which works with 200+ archive types and variants (7z, ace, arc, bz2, cab, gz, iso, paq, pea, rar, tar, wim, zip, zipx.), handles spanned archives (001, r01, z01.), supports multiple archive encryption standards, file hashing, exports tasks as console scripts.
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